Instructions to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Ollama
How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with Ollama:
```
ollama run hf.co/C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M
```
Unsloth Desktop

How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with Docker Model Runner:
```
docker model run hf.co/C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M
```

Lemonade

How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.bash2nl-qwen2.5-coder-7b-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

bash2nl — Qwen2.5-Coder-7B QLoRA, GGUF q4_K_M

Explains a Bash command line in exactly one English sentence, phrased as an instruction starting with a verb. QLoRA fine-tune of Qwen/Qwen2.5-Coder-7B-Instruct, merged and quantized to q4_K_M.

find . -name "*.py"
-> Display the names of all files in the current directory and recursively into subdirectories with names that end in .py

Usage

hf download C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF --local-dir bash2nl
cd bash2nl && ollama create bash2nl -f Modelfile
ollama run bash2nl 'ps -ef | grep nginx | awk "{print \$2}" | xargs kill -9'

The Modelfile pins the system prompt and this decoding:

option	value
`temperature`	0.0
`top_k`	1
`top_p`	1.0
`repeat_penalty`	1.0
`num_predict`	96
`num_ctx`	4096
stop	`<

Evaluation

920 held-out commands Judge columns are claude-sonnet-5 scoring a fixed 200-command subset.

metric	base	+ few-shot	this model
BLEU	14.59	17.67	33.49
chrF	44.15	45.82	52.21
ROUGE-L	39.09	40.64	53.24
judge acceptable+	0.880	0.900	0.890
judge wrong	0.120	0.100	0.110
avg words	18.0	17.2	12.4

License

Apache-2.0, matching the base model, whose weights this GGUF contains. Training data comes from the nl2bash project; consult it for the terms attached to that corpus.

Downloads last month: 65

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

4-bit

Model tree for C-H-Liu/bash2nl-qwen2.5-coder-7b-GGUF

Base model

Qwen/Qwen2.5-7B

Finetuned

Qwen/Qwen2.5-Coder-7B

Finetuned

Qwen/Qwen2.5-Coder-7B-Instruct

Quantized

(242)

this model